Evaluation of Fourier transform infrared spectroscopy and multispectral imaging as means of estimating the microbiological spoilage of farmed sea bream

Lemonia-Christina Fengou; Alexandra Lianou; Panagiotis Tsakanikas; Eleni N Gkana; Efstathios Z Panagou; George-John E Nychas

doi:10.1016/j.fm.2018.10.020

Evaluation of Fourier transform infrared spectroscopy and multispectral imaging as means of estimating the microbiological spoilage of farmed sea bream

Food Microbiol. 2019 Jun:79:27-34. doi: 10.1016/j.fm.2018.10.020. Epub 2018 Nov 3.

Authors

Lemonia-Christina Fengou¹, Alexandra Lianou², Panagiotis Tsakanikas¹, Eleni N Gkana¹, Efstathios Z Panagou¹, George-John E Nychas¹

Affiliations

¹ Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Human Nutrition, School of Food, Biotechnology and Development, Agricultural University of Athens, Athens, 11855, Greece.
² Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Human Nutrition, School of Food, Biotechnology and Development, Agricultural University of Athens, Athens, 11855, Greece. Electronic address: alianou@aua.gr.

PMID: 30621872
DOI: 10.1016/j.fm.2018.10.020

Abstract

The objective of the present study was the evaluation of Fourier transform infrared (FTIR) spectroscopy and multispectral imaging (MSI), in tandem with multivariate data analysis, as means of estimating the microbiological quality of sea bream. Farmed whole ungutted fish were stored aerobically at 0, 4 and 8 °C. At regular time intervals, fish samples (i.e. cut portions) were analysed microbiologically, while FTIR and MSI measurements also were acquired at both the skin and flesh sides of the samples. Partial least squares regression (PLSR) models were calibrated to provide quantitative estimations of the microbiological status of fish based on spectral data, in a temperature-independent manner. The PLSR model based on the FTIR data of fish skin exhibited good performance when externally validated, with the coefficient of determination (R²) and the root mean square error (RMSE) being 0.727 and 0.717, respectively. Hence, FTIR spectroscopy appears to be promising for the rapid and non-invasive monitoring of the microbiological spoilage of whole sea bream. Contrarily, the MSI models' performance was unsatisfactory, delimitating their potential exploitation in whole fish quality assessment. Model optimization results concerning fish flesh indicated that MSI may be propitious in skinned fish products, with its definite competence warranting further investigation.

Keywords: FTIR; Fish; Microbiological spoilage; Multispectral imaging; Sea bream.

Publication types

Comparative Study
Evaluation Study

MeSH terms

Animals
Aquaculture / methods*
Colony Count, Microbial
Food Microbiology / methods*
Food Preservation
Hydrogen-Ion Concentration
Least-Squares Analysis
Optical Imaging*
Sea Bream*
Seafood / microbiology*
Spectroscopy, Fourier Transform Infrared*
Temperature